set_scenario_dataset

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must carry the full behavioral disclosure burden. It only states 'Add or replace', which implies mutation but does not explain side effects, whether existing datasets are overwritten, permission requirements, or error behavior. It does clarify the dataset is 'referenceable' but offers no detail on lifecycle or consequences. This is a significant transparency gap for a write operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the action and purpose, then adds the clarifying detail about referenceability and the sibling analogy. It is concise and information-dense without excess words, though it could be slightly clearer if broken into two sentences. Still, it earns a high score for efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with 4 parameters, no output schema, and no annotations, the description is too thin. It does not explain the structure of the 'value' object, the format of 'scenarioId', return behavior, or error cases. The referenceability note is useful but does not complete the picture. An agent would need to inspect sibling tools or infer too much to call this correctly with confidence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25% (only 'project' has a description). The description itself does not map parameters beyond implying 'name' and 'value' are the dataset name and values, and 'scenarioId' is likely the target scenario, but none of this is explicit. The analogy to set_flow_dataset may help if that sibling is documented, but the description does not compensate for the low schema coverage. An agent would struggle to know the exact format of 'value' or the expected 'scenarioId'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('Add or replace') and resource ('named scenario-data dataset'), then clarifies its purpose as 'a set of scenario-level param values, referenceable from any flow entry's own params/postprocess expressions'. It also explicitly references the sibling set_flow_dataset, distinguishing it by level ('one level up'). This leaves no ambiguity about what the tool does or how it differs from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The analogy 'mirrors set_flow_dataset one level up' provides strong contextual guidance, implying this tool is for scenario-level datasets while the sibling handles flow-level. This effectively tells the agent when to use it versus the flow-level alternative. However, it does not explicitly state when not to use it or mention the removal counterpart (remove_scenario_dataset), though the usage context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.